dr什么箱型Matlab数据降维工具箱drtoolbox 安装备忘

常用Matlab降维软件包包括真实有效的多种降维算法：
– Principal Component Analysis ('PCA')
– Linear Discriminant Analysis ('LDA')
– Multidimensional scaling ('MDS')
– Isomap ('Isomap')
– Landmark Isomap ('LandmarkIsomap')
– Locally Linear Embedding ('LLE')
– Laplacian Eigenmaps ('Laplacian')
– Hessian LLE ('HessianLLE')
– Local Tangent Space Alignment ('LTSA')
– Diffusion maps ('DiffusionMaps')
– Kernel PCA ('KernelPCA')
– Generalized Discriminant Analysis ('KernelLDA')
– Stochastic Neighbor Embedding ('SNE')
– Neighborhood Preserving Embedding ('NPE')
– Linearity Preserving Projection ('LPP')
– Stochastic Proximity Embedding ('SPE')
– Linear Local Tangent Space Alignment ('LLTSA')
– Simple PCA ('SimplePCA')
– Probabilistic PCA ('ProbPCA')
– Conformal Eigenmaps ('CCA', implemented as an extension of LLE)
– Maximum Variance Unfolding ('MVU', implemented as an extension of LLE)
– Fast Maximum Variance Unfolding ('FastMVU')
– Locally Linear Coordination ('LLC')
– Manifold charting ('ManifoldChart')
– Coordinated Factor Analysis ('CFA')
– Autoencoders using RBM pretraining ('AutoEncoderRBM')
– Autoencoders using evolutionary optimization ('AutoEncoderEA')